A delay-dependent approach to robust stability for uncertain hybrid bidirectional associative memory neural networks with time-varying delays

Chien-Yu Lu, Koan Yuh Chang, Hsun Heng Tsai, Wen Jer Chang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper performs a global robust stability analysis of a particular class of hybrid bidirectional associative memory time-varying delayed neural network with norm-bounded timevarying parameter uncertainties. The activation functions are assumed to be globally Lipschitz continuous. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing relaxation matrices which, when chosen properly, produce a less conservative result. Two numerical examples are given to illustrate the significant improvement obtained in the conservativeness of the delay bound.

Original languageEnglish
Pages (from-to)164-171
Number of pages8
JournalJournal of Marine Science and Technology
Volume18
Issue number2
Publication statusPublished - 2010 Apr 1

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Neural networks
Data storage equipment
matrix
Stability criteria
Linear matrix inequalities
stability analysis
Chemical activation
Robust stability
Uncertainty
norm
parameter

All Science Journal Classification (ASJC) codes

  • Oceanography
  • Ocean Engineering
  • Mechanics of Materials
  • Mechanical Engineering

Cite this

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A delay-dependent approach to robust stability for uncertain hybrid bidirectional associative memory neural networks with time-varying delays. / Lu, Chien-Yu; Chang, Koan Yuh; Tsai, Hsun Heng; Chang, Wen Jer.

In: Journal of Marine Science and Technology, Vol. 18, No. 2, 01.04.2010, p. 164-171.

Research output: Contribution to journalArticle

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